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#Graphs

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Came up at work but definitely a question of general interest:

I feel like when looking at a line-by-line diff of an XML file, it's just...
really not super clear, even with highlighting and such. Is there any sort of graph-aware diff tool that might generate a visual graph and show the difference that way? So that rather than reviewing line by line, you can say "ah, a node has moved from being a child of this node to another", or "these two nodes have been merged into one".

I feel like it would be possible to gin something up in like, networkX or something, but if there's prior art...

#techPosting #XML #computerScienceTrees #graphs #diffs

Is there a way to graph trending hashtags on mastodon/the Fediverse?

What I'm interested in is to graph say my local city of #Adelaide and use that as a bit of an indicator of if #Mastodon usage and engagemement is growing locally in my town

And yes im interested in data across the fediverse or at least across a few selected servers, as I want data beyond just a single instance.

I can see this on my desktop web interface right now.. so Im guessing there *should* be a way.

Talk me out of building a #Neo4j implementation in parallel to my existing #PostgreSQL DB (with a subset of tables as nodes) for queries that tend to be "graph-like" in nature.

In particular, I'm thinking of failure analysis, predictive maintenance, etc in relation to physical infrastructure I model as a directed acyclic graph.

Is this just my #ADHD wanting to try something new, or could I actually find value in this side-quest? 😬

#Dev #Graphs #Godot #GDScript

Basic graph:

A ---------------------> C
| ^
'---------> B ------------'

A goes to B and C. B goes to C.

Say I change A. How do I get a result in C? What are the ways to make it "run"?

I can do a recursive loop, but it gets hard to reason about.

Are there words for this I can search up?

Could it be done with signals?

Also, is there some clever way to detect infinite loops?

graph-plexed
🦇

Graphs are everywhere, but LLMs are trained on text. In „Talk like a Graph“ (ICLR 2024), Google introduces methods for encoding graphs for LLMs, launches the GraphQA benchmark, and demonstrates how task phrasing & graph structure impact reasoning. Right methods boost performance by up to 60%! #ICLR2024 #AI #Graphs
blog.research.google/2024/03/t

blog.research.googleTalk like a graph: Encoding graphs for large language models